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What is SpiderGate?

SpiderGate is an OpenAI-compatible LLM gateway. You point your existing OpenAI client at one base URL, send a request with a task name like spideriq/coding, and SpiderGate routes it to the best available model across dozens of providers — handling auth, failover, cost tracking, and observability for you.

It is built for AI agents and the apps that run them. Anything that speaks the OpenAI chat-completions protocol works unchanged: swap the base URL and the API key, keep your code.

curl -X POST "https://spideriq.ai/api/gate/v1/chat/completions" \
  -H "Authorization: Bearer $SPIDERIQ_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "spideriq/coding",
    "messages": [{"role": "user", "content": "Write a Python function that reverses a string"}]
  }'

What you get

  • One endpoint, every provider. A single OpenAI-compatible API in front of Groq, Mistral, OpenRouter, Cerebras, NVIDIA NIM, and more — plus subscription primaries like Codex.

  • Task-based routing. Ask for a job (spideriq/extraction, agent/chat) instead of a specific model. SpiderGate picks the right model and falls back automatically when one is busy or down.

  • A key vault. Store every provider key in one encrypted place, share keys across a pool, or bring your own — no more keys scattered across .env files.

  • Per-agent control. Mint tokens with monthly budgets, rate limits, and model restrictions, and watch spend per agent.

  • Full observability. Every request is traced — what was sent, what came back, which model served it, latency, tokens, and cost.

Why a gateway

Calling LLM providers directly means managing a different SDK, key, rate limit, and failure mode for each one — and rewriting code every time you switch models. SpiderGate collapses that into a single, stable interface:

  • You write to one protocol. The OpenAI chat-completions shape, which almost every tool already speaks.

  • Routing is a config concern, not a code concern. Change which model serves spideriq/coding without touching your app.

  • Failover is automatic. When a provider rate-limits or errors, the request falls through a chain of alternatives before it ever fails.

When to use SpiderGate

SpiderGate is a strong fit when you want to:

  • Run AI agents or workers that call LLMs and need reliable, multi-provider access behind one URL.

  • Maximize free tiers by rotating across many provider keys before paying for premium models.

  • Control and observe spend per agent, with budgets, rate limits, and per-request traces.

  • Centralize provider keys in an encrypted vault instead of spreading them across services.

It may not be the right fit if you need a self-hosted, on-premises model-serving stack (SpiderGate is a managed gateway), or if you only ever call a single model from a single provider and don't need routing, pooling, or observability.

How this manual is organized

  • Getting Started — what SpiderGate is, a quickstart, and the core concepts.

  • Using the Gateway — chat completions, streaming, task aliases, models, and multi-modal endpoints.

  • Dashboard — the overview, agent keys, the vault, and the playground.

  • Observability — request traces.

  • Reference — the full API, authentication, errors, and rate limits.

Next steps

  1. Send your first request with the Quickstart.

  2. Learn the Core Concepts — aliases, providers, and tokens.

  3. Browse the Task Aliases to pick the right one for your job.